UM
Status已發表Published
Affiliated with RCfalse
Rule Generation and Evaluation by Data Mining Ensembles for Clinical Decision Support
Simon Fong1; Luke Lu1; Kun Lan1; Osama Mohammed3; Jinan Fiaidhi2; Sabah Mohammed2
2013-09-18
Conference NameIASTED International Conference Biomedical Engineering (BioMed 2013)
Source PublicationProceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2013
Pages33-40
Conference DateFebruary 13 - 15, 2013
Conference PlaceInnsbruck, Austria
Abstract

Clinical decision support systems (CDSS) often base on rules that are inferred from collected patients' histories, together with expert judgements and consented medical guidelines. This type of advisor system is known as rule-based reasoning system or expert system which classifies a given test instance into a particular outcome from the learned rules. The test instance carries multiple attributes which are usually the values of diagnostic tests. In this paper, we propose a classifier ensemble-based method for supporting disease diagnosis. The ensemble data mining learning methods are applied for rule generation, and a multi-criteria evaluation approach is used for selecting reliable rules over the results of the ensemble methods. The efficacy of the proposed methodology is illustrated via an example of a thyroid disease classification.

KeywordEnsemble Data Mining Clinical Decision Support Rule-based System Medical Informatics
DOI10.2316/P.2013.791-090
URLView the original
Language英語English
Fulltext Access
Citation statistics
Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Department of Computer and Information Science University of Macau Macau SAR
2.Department of Computer Science, Lakehead University Thunder Bay, Canada
3.Department of Software Engineering, Lakehead University, Thunder Bay, Canada
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Simon Fong,Luke Lu,Kun Lan,et al. Rule Generation and Evaluation by Data Mining Ensembles for Clinical Decision Support[C],2013:33-40.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Simon Fong]'s Articles
[Luke Lu]'s Articles
[Kun Lan]'s Articles
Baidu academic
Similar articles in Baidu academic
[Simon Fong]'s Articles
[Luke Lu]'s Articles
[Kun Lan]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Simon Fong]'s Articles
[Luke Lu]'s Articles
[Kun Lan]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.